Using deep learning to automatically generate design starting points for free-form imaging optical systems: retraction.

The referenced article [Appl. Opt.61, 6241 (2022)APOPAI0003-693510.1364/AO.460977] has been retracted by the authors.

Using deep learning to automatically generate design starting points for free-form imaging optical systems.

In this paper, we propose a method to automatically generate design starting points for free-form three-mirror imaging systems with different folding configurations using deep neural networks. For a given range of system parameters, a large number of datasets are automatically generated using the double seed extended curve algorithm and coded optimization. Deep neural networks are then trained using a supervised learning approach and can be used to generate good design starting points directly. The feasibility of the method is verified by designing a free-form three-mirror system with three different folding configurations. This method can significantly reduce the design time and effort for free-form imaging systems, and can be extended to complex optical systems with more optical surfaces.

Comprehensive evaluation of protein-coding sORFs prediction based on a random sequence strategy.

Background: Small open reading frames (sORFs) with protein-coding ability present unprecedented challenge for genome annotation because of their short sequence and low expression level. In the past decade, only several prediction methods have been proposed for discovery of protein-coding sORFs and lack of objective and uniform negative datasets has become an important obstacle to sORFs prediction. The prediction efficiency of current sORFs prediction methods needs to be further evaluated to provide better research strategies for protein-coding sORFs discovery. Methods: In this work, nine mainstream existing methods for predicting protein-coding potential of ORFs are comprehensively evaluated based on a random sequence strategy. Results: The results show that the current methods perform poorly on different sORFs datasets. For comparison, a sequence based prediction algorithm trained on prokaryotic sORFs is proposed and its better prediction performance indicates that the random sequence strategy can provide feasible ideas for protein-coding sORFs predictions. Conclusions: As a kind of important functional genomic element, discovery of protein-coding sORFs has shed light on the dark proteomes. This evaluation work indicates that there is an urgent need for developing specialized prediction tools for protein-coding sORFs in both eukaryotes and prokaryotes. It is expected that the present work may provide novel ideas for future sORFs researches.

Hepatoprotection of Lycii Fructus Polysaccharide against Oxidative Stress in Hepatocytes and Larval Zebrafish.

Scavenging of oxidative stress by antioxidants may provide a therapeutic strategy for nonalcoholic fatty liver disease (NAFLD). Increasing evidence is supporting the potential application of natural resourced polysaccharides as promising prevention or treatment strategies against NAFLD. In the current study, an acidic heteropolysaccharide, LFP-a1, was isolated and purified from Lycii fructus with successively hot water refluxing extraction, alcohol precipitation, protein removal, and DEAE-52 cellulose chromatographic separation. LFP-a1 was a complicated structured polysaccharide with an average MW of 4.74 × 104 Da and composed of 6 monosaccharides and 1 uronic acid. Preexposure of LFP-a1 could increase the cell viability and reverse the abnormal oxidative stress though inhibition of mitochondrial-mediated apoptotic pathway and correction of cell cycle progression against H2O2 hepatoxicity in NAFLD model L02 cells. Consistently, in vivo study in thioacetamide- (TAA-) induced NAFLD model zebrafish larvae showed LFP-a1 preserved the liver integrity and alleviated TAA-induced oxidative stress through downregulation of abnormal apoptosis. These observations indicated the hepatoprotective activity of LFP-a1, which may be applied for the prevention or treatment of NAFLD or other oxidative stress-related diseases.

Integrative omics analysis reveals relationships of genes with synthetic lethal interactions through a pan-cancer analysis.

Synthetic lethality is thought to play an important role in anticancer therapies. Herein, to understand the potential distributions and relationships between synthetic lethal interactions between genes, especially for pairs deriving from different sources, we performed an integrative analysis of genes at multiple molecular levels. Based on inter-species phylogenetic conservation of synthetic lethal interactions, gene pairs from yeast and humans were analyzed; a total of 37,588 candidate gene pairs containing 7,816 genes were collected. Of these, 49.74% of genes had 2-10 interactions, 22.93% were involved in hallmarks of cancer, and 21.61% were identified as core essential genes. Many genes were shown to have important biological roles via functional enrichment analysis, and 65 were identified as potentially crucial in the pathophysiology of cancer. Gene pairs with dysregulated expression patterns had higher prognostic values. Further screening based on mutation and expression levels showed that remaining gene pairs were mainly derived from human predicted or validated pairs, while most predicted pairs from yeast were filtered from analysis. Genes with synthetic lethality were further analyzed with their interactive microRNAs (miRNAs) at the isomiR level which have been widely studied as negatively regulatory molecules. The miRNA-mRNA interaction network revealed that many synthetic lethal genes contributed to the cell cycle (seven of 12 genes), cancer pathways (five of 12 genes), oocyte meiosis, the p53 signaling pathway, and hallmarks of cancer. Our study contributes to the understanding of synthetic lethal interactions and promotes the application of genetic interactions in further cancer precision medicine.

An acidic heteropolysaccharide from Lycii fructus: Purification, characterization, neurotrophic and neuroprotective activities in vitro.

Regeneration of neurites network constitutes a neurotrophic and therapeutic strategy for Parkinson's disease (PD). Increasing evidence is supporting the potential application of natural polysaccharides in prevention or treatment of PD. In this study, an acidic heteropolysaccharide LFP-1 was isolated from Lycii fructus, and purified by ion-exchange and gel filtration chromatography. Structural features of LFP-1 were analyzed with molecular weight (MW) distribution, monosaccharide composition, methylation and nuclear magnetic resonance (NMR) spectra. LFP-1 was a complicated structured polysaccharide with an average MW of 1.78 × 104 Da and composed of highly branched arabinogalactans, homogalacturonan and rhamnogalacturonan moieties. LFP-1 promoted neuronal differentiation and neurite outgrowth in vitro in PC12 cell models. Furthermore, LFP-1 had a significantly protective effect against 1-methyl-4-phenylpyridiniumion (MPP+)-induced neurotoxicity in PD model PC12 cells. These observations unambiguously indicated the neurotrophic and neuroprotective activities of LFP-1, which may be developed for prevention or treatment of neurodegeneration in PD.

Construction and Analysis of a ceRNA Network Reveals Potential Prognostic Markers in Colorectal Cancer.

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide and is derived from an accumulation of genetic and epigenetic changes. This study explored potential prognostic markers in CRC via the construction and in-depth analysis of a competing endogenous RNA (ceRNA) network, which was generated through a three-step process. First, we screened candidate hub genes in CRC as the primary gene markers to survey their related regulatory non-coding RNAs, miRNAs. Second, the interacting miRNAs were used to search for associated lncRNAs. Thus, candidate RNAs were first constructed into ceRNA networks based on close associations with miRNAs. Further analysis at the isomiR level was also performed for each miRNA locus to understand the detailed expression patterns of the multiple variants. Finally, RNAs were performed an in-depth analysis of expression correlations, which contributed to further screening and validation of potential RNAs with close correlations to each other. Using this approach, nine hub genes, 13 related miRNAs, and 29 candidate lncRNAs were collected and used to construct the ceRNA network. Further in-depth analysis identified the MFAP5-miR-200b-3p-AC005154.6 axis as a potential prognostic marker in CRC. MFAP5 and miR-200b-3p have previously been reported to play important roles in tumorigenesis. These RNAs showed potential prognostic values, and the combination of them may have more sensitivity than using them alone. In conclusion, MFAP5, miR-200b-3p, and AC005154.6 may have potential prognostic value in CRC and may provide a prognostic reference for this patient population.

Screening and identification of genes associated with cell proliferation in cholangiocarcinoma.

Cholangiocarcinoma (CCA), an aggressive tumor with poor prognosis, is a malignant cancer with increasing incidence and mortality rates. It is important to survey crucial genes in CCA to find and design potential drug targets, especially for those genes associated with cell proliferation that is a key biological process in tumorgenesis. Herein, we surveyed genes associated with cell proliferation via a comprehensive pan-cancer analysis. Candidate genes were further analyzed using multiple approaches, including cross-analysis from diverse molecular levels, examination of potential function and interactions, and additional experimental validation. We primarily screened 15 potential genes based on 11 validated genes, and these 26 genes were further examined to delineate their biological functions and potential roles in cancer treatment. Several of them were involved synthetically lethal genetic interactions, especially for RECQL4, TOP2A, MKI67 and ASPM, indicating their potential roles in drug design and cancer treatment. Further experimental validation indicated that some genes were significantly upregulated in several cancer cell lines, implying their important roles in tumorigenesis. Our study identifies some genes associated with cell proliferation, which may be potential future targets in molecular targeted therapy.

Anti-tumor effect of Liqi, a traditional Chinese medicine prescription, in tumor bearing mice.

BACKGROUND: Liqi, an herbal preparation used in traditional Chinese medicine, has been used to treat cancer in China for centuries. We investigated the anti-tumor effects of liqi and their mechanisms in mice that had been xenografted with tumors. METHODS: Sarcoma 180 tumor, Lewis lung carcinoma, and SGC-7901 cells were implanted in BALB/c mice, C57BL/6 mice, and BALB/c nude mice, respectively. Liqi was administered to subgroups of these mice. The tumor weight and size were measured. Cell cycle analysis and T lymphocyte subsets were determined by flow cytometry. The activity of NK cells and TNF was tested using cytotoxicity assay on YAC-1 cells and L929 cells, respectively, and the activity of IL-2 was tested with an IL-2-dependent CTLL-2 cell proliferation assay. Platelet aggregation was monitored by measuring electric impedance, and the levels of thromboxane A2 (TXA2) and prostacyclin (PGI2) in blood were measured by 125I-TXB2 and 125I-Keto-PGF1alpha radioimmunoassay. RESULTS: The results showed that liqi inhibited tumor growth in tumor-implanted mice and arrested the cell proliferation in the G0/G1 phase and reduced the portion of cells in S and G2/M phase for SGC-7901 cells. Liqi increased the activity of NK cells and TNF-alpha, stimulated IL-2 production and activity, and regulated T lymphocyte subpopulations. Liqi inhibited the Lewis lung carcinoma metastasis by inhibiting platelet aggregation and normalizing the balance between TXA2 and PGI2. CONCLUSION: All these findings demonstrated that liqi has an anti-tumor effect in vivo. The mechanism may be related to immune regulation and anticoagulation effects.